Typically, enterprise applications organize data in a hierarchical manner in order to facilitate accessing, manipulating, visualizing, and understanding of the data and associated information. Hierarchical organization of a dataset is designed and implemented manually and then represented explicitly in the form of, for example, a data warehouse, an online analytical processing (OLAP) cube, meta-data associated with an ad-hoc relational schema, etc. Such approaches are problematic because they involve significant overhead for design, implementation, maintenance, and so forth. Hence, a method for reducing or even eliminating the overhead associated with design of hierarchical data organizations and minimizing the overhead associated with implementation is needed in the art.